Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "146"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 146 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 88 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 86 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])]) 

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 146, Node N14:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459905 digital_ok 100.00% 100.00% 0.00% 0.00% - - 11.222831 2.062647 3.487207 1.044269 12.234494 -1.216437 -0.007419 -1.286590 0.0363 0.6871 0.4914 nan nan
2459904 digital_ok 100.00% 100.00% 0.00% 0.00% - - 10.976570 2.010965 3.835416 1.329753 8.933279 -0.601528 0.713915 -2.563745 0.0367 0.6869 0.4931 nan nan
2459903 digital_ok 100.00% 100.00% 0.00% 0.00% - - 11.700894 2.170030 3.892998 1.011987 7.174490 -0.505260 0.887067 -2.686552 0.0371 0.6894 0.5120 nan nan
2459902 digital_ok 100.00% 100.00% 0.00% 0.00% - - 13.301611 2.702526 4.079172 1.429914 7.761811 -0.676198 0.361811 -1.672315 0.0401 0.6904 0.5098 nan nan
2459901 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.699534 1.664788 -1.522950 0.662176 0.845884 -1.169747 1.446195 -1.899978 0.6328 0.6838 0.4193 nan nan
2459900 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.113182 1.459163 -1.445085 0.688898 0.438335 -0.920086 0.321857 -1.798308 0.5913 0.6533 0.3496 nan nan
2459898 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.227786 1.152016 -1.633162 0.747333 -0.071346 -1.324248 -0.002536 -2.247662 0.6456 0.6939 0.4066 nan nan
2459897 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.275121 1.188359 -1.668448 0.914850 -0.624371 -0.955651 0.334594 -2.282454 0.1010 0.1197 0.0548 nan nan
2459896 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.004576 1.329176 -1.671049 0.937330 -0.794360 -1.531837 -0.043724 -1.639437 0.0999 0.1140 0.0525 nan nan
2459895 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.318098 0.958281 -1.726955 1.833703 -0.421830 -0.171725 -1.884193 0.484220 0.1114 0.1282 0.0346 nan nan
2459894 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.333531 1.217780 -1.529503 0.856678 -0.448507 -1.194829 0.256120 -2.199507 0.1017 0.1151 0.0498 nan nan
2459893 digital_ok 0.00% 38.49% 38.49% 0.00% - - -0.112452 1.300633 -1.606534 0.678657 -0.533525 -1.213404 0.008464 -2.530768 0.4653 0.4899 0.2580 nan nan
2459892 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.011255 1.309914 -1.892218 0.966248 0.669324 -1.003823 -0.105448 -2.405611 0.6571 0.6995 0.3907 nan nan
2459891 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.067478 1.021531 -1.860822 1.170873 0.442497 -1.141120 -0.004066 -1.913772 0.6501 0.6956 0.3962 nan nan
2459890 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.248244 1.046265 -1.926435 1.730112 0.077643 -1.064364 0.708997 -1.087683 0.6489 0.6937 0.3963 nan nan
2459889 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.208538 1.151233 -1.911166 1.104184 -0.509165 -1.281256 -0.057743 -2.706080 0.6589 0.6986 0.3919 nan nan
2459888 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.045160 0.906360 -1.857964 1.536025 -0.596093 -1.033774 -0.760842 -0.784324 0.6784 0.7135 0.3839 nan nan
2459887 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.006585 0.763230 -1.748722 0.780660 -1.218903 -1.650748 -0.094876 -1.533122 0.6618 0.6985 0.3934 nan nan
2459886 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.638546 0.945657 -1.518109 1.145866 -2.024161 0.308826 -1.451006 -0.282474 0.7540 0.7581 0.3241 nan nan
2459885 digital_ok 100.00% 0.00% 0.00% 0.00% - - 2.232008 3.150252 7.137951 30.100266 1.774593 5.432572 2.236833 5.182172 0.7189 0.7368 0.3441 nan nan
2459884 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.681848 4.619191 -0.105304 4.661808 -0.446535 5.239465 -0.763065 -3.406010 0.6787 0.6805 0.3861 nan nan
2459883 digital_ok 100.00% 0.00% 0.00% 0.00% - - 1.057583 7.462584 17.312333 41.419800 1.240675 7.541308 -0.650059 -6.293574 0.6855 0.6897 0.3736 nan nan
2459882 digital_ok 100.00% 0.00% 0.00% 0.00% - - 1.535877 12.043612 19.204940 48.558674 2.383712 10.541547 1.593897 -2.773263 0.6884 0.6958 0.3692 nan nan
2459881 digital_ok 100.00% 0.00% 0.00% 0.00% - - 0.582591 7.754697 21.797512 54.818014 2.956958 20.338903 0.378033 1.621760 0.7243 0.7402 0.3200 nan nan
2459880 digital_ok 100.00% 0.00% 0.00% 0.00% - - 0.721808 8.437421 17.791784 44.378717 2.158732 6.506531 -0.321799 -3.877408 0.6826 0.6927 0.3842 nan nan
2459879 digital_ok 0.00% 0.00% 0.00% 0.00% - - -1.288895 3.426176 -2.337281 1.868955 -0.296760 -0.330627 -0.733047 -4.539379 0.6675 0.6801 0.4009 nan nan
2459878 digital_ok 100.00% 0.00% 0.00% 100.00% - - 4.384917 7.399156 41.581275 51.565712 4.611827 12.850746 -3.632006 -6.882099 0.2694 0.2652 -0.2791 nan nan
2459876 digital_ok 100.00% 0.00% 0.00% 100.00% - - 4.649231 7.145446 29.695605 35.724585 10.443904 35.229634 -3.177434 -5.970377 0.2930 0.2835 -0.2804 nan nan
2459875 digital_ok 100.00% 0.00% 0.00% 100.00% - - 4.833955 7.219080 40.104959 48.771853 4.108412 17.715354 -0.725041 4.061925 0.3078 0.3010 -0.2855 nan nan
2459874 digital_ok 100.00% 0.00% 0.00% 100.00% - - 6.874515 10.232680 20.682236 24.971760 5.383243 22.348143 -2.591554 -4.859304 0.2947 0.2904 -0.2895 nan nan
2459873 digital_ok 100.00% 0.00% 0.00% 100.00% - - 4.988978 7.218835 27.824572 33.605619 2.237567 9.191835 -1.990780 -3.041155 0.3193 0.3154 -0.2917 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 146: 2459905

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok ee Temporal Variability 12.234494 2.062647 11.222831 1.044269 3.487207 -1.216437 12.234494 -1.286590 -0.007419

Antenna 146: 2459904

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok ee Shape 10.976570 2.010965 10.976570 1.329753 3.835416 -0.601528 8.933279 -2.563745 0.713915

Antenna 146: 2459903

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok ee Shape 11.700894 2.170030 11.700894 1.011987 3.892998 -0.505260 7.174490 -2.686552 0.887067

Antenna 146: 2459902

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok ee Shape 13.301611 13.301611 2.702526 4.079172 1.429914 7.761811 -0.676198 0.361811 -1.672315

Antenna 146: 2459901

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.664788 0.699534 1.664788 -1.522950 0.662176 0.845884 -1.169747 1.446195 -1.899978

Antenna 146: 2459900

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.459163 0.113182 1.459163 -1.445085 0.688898 0.438335 -0.920086 0.321857 -1.798308

Antenna 146: 2459898

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.152016 1.152016 0.227786 0.747333 -1.633162 -1.324248 -0.071346 -2.247662 -0.002536

Antenna 146: 2459897

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.188359 1.188359 0.275121 0.914850 -1.668448 -0.955651 -0.624371 -2.282454 0.334594

Antenna 146: 2459896

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.329176 1.329176 -0.004576 0.937330 -1.671049 -1.531837 -0.794360 -1.639437 -0.043724

Antenna 146: 2459895

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 1.833703 0.318098 0.958281 -1.726955 1.833703 -0.421830 -0.171725 -1.884193 0.484220

Antenna 146: 2459894

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.217780 1.217780 0.333531 0.856678 -1.529503 -1.194829 -0.448507 -2.199507 0.256120

Antenna 146: 2459893

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.300633 -0.112452 1.300633 -1.606534 0.678657 -0.533525 -1.213404 0.008464 -2.530768

Antenna 146: 2459892

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.309914 1.309914 0.011255 0.966248 -1.892218 -1.003823 0.669324 -2.405611 -0.105448

Antenna 146: 2459891

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 1.170873 -0.067478 1.021531 -1.860822 1.170873 0.442497 -1.141120 -0.004066 -1.913772

Antenna 146: 2459890

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 1.730112 1.046265 0.248244 1.730112 -1.926435 -1.064364 0.077643 -1.087683 0.708997

Antenna 146: 2459889

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 1.151233 0.208538 1.151233 -1.911166 1.104184 -0.509165 -1.281256 -0.057743 -2.706080

Antenna 146: 2459888

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 1.536025 0.906360 0.045160 1.536025 -1.857964 -1.033774 -0.596093 -0.784324 -0.760842

Antenna 146: 2459887

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 0.780660 0.763230 0.006585 0.780660 -1.748722 -1.650748 -1.218903 -1.533122 -0.094876

Antenna 146: 2459886

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 1.145866 -0.638546 0.945657 -1.518109 1.145866 -2.024161 0.308826 -1.451006 -0.282474

Antenna 146: 2459885

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 30.100266 3.150252 2.232008 30.100266 7.137951 5.432572 1.774593 5.182172 2.236833

Antenna 146: 2459884

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Temporal Variability 5.239465 4.619191 -0.681848 4.661808 -0.105304 5.239465 -0.446535 -3.406010 -0.763065

Antenna 146: 2459883

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 41.419800 7.462584 1.057583 41.419800 17.312333 7.541308 1.240675 -6.293574 -0.650059

Antenna 146: 2459882

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 48.558674 12.043612 1.535877 48.558674 19.204940 10.541547 2.383712 -2.773263 1.593897

Antenna 146: 2459881

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 54.818014 7.754697 0.582591 54.818014 21.797512 20.338903 2.956958 1.621760 0.378033

Antenna 146: 2459880

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 44.378717 8.437421 0.721808 44.378717 17.791784 6.506531 2.158732 -3.877408 -0.321799

Antenna 146: 2459879

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Shape 3.426176 3.426176 -1.288895 1.868955 -2.337281 -0.330627 -0.296760 -4.539379 -0.733047

Antenna 146: 2459878

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 51.565712 7.399156 4.384917 51.565712 41.581275 12.850746 4.611827 -6.882099 -3.632006

Antenna 146: 2459876

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 35.724585 4.649231 7.145446 29.695605 35.724585 10.443904 35.229634 -3.177434 -5.970377

Antenna 146: 2459875

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 48.771853 4.833955 7.219080 40.104959 48.771853 4.108412 17.715354 -0.725041 4.061925

Antenna 146: 2459874

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 24.971760 6.874515 10.232680 20.682236 24.971760 5.383243 22.348143 -2.591554 -4.859304

Antenna 146: 2459873

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
146 N14 digital_ok nn Power 33.605619 4.988978 7.218835 27.824572 33.605619 2.237567 9.191835 -1.990780 -3.041155

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